We study a family of graph clustering problems where each cluster has to satisfy a certain local requirement. Formally, let µ be a function on the subsets of vertices of a graph G...
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
In this paper, we describe NoCGEN, a Network On Chip (NoC) generator, which is used to create a simulatable and synthesizable NoC description. NoCGEN uses a set of modularised rou...
Compression of term frequency lists and very long document-id lists within an inverted file search engine are examined. Several compression schemes are compared including Elias γ...
All existing methods for thermal-via allocation are based on a steady-state thermal analysis and may lead to excessive number of thermal vias. This paper develops an accurate and ...